Motion planning using binary space partitioning

This work explores a method for path planning for a robot in an environment that consists of stationary and moving obstacles. The technique uses binary partitioning of the environment by the obstacles to establish and analyze the spatial relationship between robot and obstacles. Hyperplanes are used to obtain recursively a disjoint set of D-dimensional cells, with each cell designated as belonging to either the interior or the exterior of the set. An overt idea of binary space partitioning as a representation of polytopes is given. Thus, the space-time configuration of free space is viewed as disjoint polytopes; each point in space-time is considered a map into a unique polytope. A traversal of the tree is used to obtain a linear order which gives the collision probability with the environment. Adjacent polytopes between the start and goal polytopes are then utilized to obtain a trajectory. Current implementation for a 2D static environment is discussed.<<ETX>>

[1]  Andrew K. C. Wong,et al.  Structuring Free Space as a Hypergraph for Roving Robot Path Planning and Navigation , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  John Amanatides,et al.  Merging BSP trees yields polyhedral set operations , 1990, SIGGRAPH.

[3]  Tomás Lozano-Pérez,et al.  An algorithm for planning collision-free paths among polyhedral obstacles , 1979, CACM.

[4]  Paul M. Griffin,et al.  Path planning for a mobile robot , 1992, IEEE Trans. Syst. Man Cybern..

[5]  Larry S. Davis,et al.  Multiresolution path planning for mobile robots , 1986, IEEE J. Robotics Autom..

[6]  Meghanad D. Wagh,et al.  Robot path planning using intersecting convex shapes: Analysis and simulation , 1987, IEEE J. Robotics Autom..

[7]  King-Sun Fu,et al.  A hierarchical orthogonal space approach to three-dimensional path planning , 1986, IEEE J. Robotics Autom..

[8]  Rodney A. Brooks,et al.  Solving the Find-Path Problem by Good Representation of Free Space , 1983, Autonomous Robot Vehicles.

[9]  James L. Crowley,et al.  Navigation for an intelligent mobile robot , 1985, IEEE J. Robotics Autom..

[10]  S. Sitharama Iyengar,et al.  Robot navigation in unknown terrains using learned visibility graphs. Part I: The disjoint convex obstacle case , 1987, IEEE Journal on Robotics and Automation.

[11]  Pradeep K. Khosla,et al.  Superquadric artificial potentials for obstacle avoidance and approach , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.

[12]  Henry Fuchs,et al.  On visible surface generation by a priori tree structures , 1980, SIGGRAPH '80.

[13]  Martin Herman,et al.  Fast, three-dimensional, collision-free motion planning , 1986, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[14]  J. Schwartz,et al.  On the “piano movers'” problem I. The case of a two‐dimensional rigid polygonal body moving amidst polygonal barriers , 1983 .

[15]  Narendra Ahuja,et al.  Path planning using the Newtonian potential , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[16]  Rodney A. Brooks,et al.  A subdivision algorithm in configuration space for findpath with rotation , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[17]  Alade O. Tokuta,et al.  Scanline algorithms in robot path planning , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[18]  Charles E. Thorpe,et al.  Path Relaxation: Path Planning for a Mobile Robot , 1984, AAAI.

[19]  Rodney A. Brooks,et al.  Natural decomposition of free space for path planning , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.